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Crowdsourcing as a model for protein structure discovery

Protein structure research often involves running complex algorithms on massive supercomputers buried deep within the bowels of some of the nations top academic institutions. Such initiatives are expensive to run and require a significant amount of financial capital and technical support. In order to defray the cost of protein structure research, scientists have come with several alternative methods to supercomputing which ultimately result in faster time to results at a fraction of the cost of supercomputing.

One such technique , which we have discussed in the past (see Foldit! Guilt-Free Computer Gaming for Protein Scientists), was adapted from the world of crowdsourcing and involves tapping in on the brainpower of thousands of individuals from around the world to solve the puzzle of numerous protein structures in an interactive, online gaming platform. At the same time, these individuals are helping refine algorithms used by protein folding software enabling them to become more efficient at solving structural proteomic problems.

Folding@home is another interesting initiative that began around a decade ago by scientists in the Pande Lab at Stanford University. According to the project’s website, Folding@home is a distributed computing project — people from throughout the world download and run software to band together to make one of the largest supercomputers in the world. Folding@home uses novel computational methods coupled to distributed computing, to simulate problems millions of times more challenging than previously achieved.

The project requests that owners of personal computers download the Folding@home software which will allow the Folding@home algorithm to be run on the owner’s local processor. The data will then be fed back to the Folding@home database allowing for many protein folding simulations to be run simultaneously thereby exponentially increasing the amount of daily data added to the publicly available protein structure database.